Visible-infrared cross-modality person re-identification (VI-ReID) is currently a prevalent but
challenging research topic in computer vision, since it can remedy the poor performance of …

Abstract RGB-Thermal infrared (RGB-T) image analysis has been actively studied in recent
years. In the past decade, it has received wide attention and made a lot of important …

Visible-infrared person re-identification (Re-ID) aims to match the pedestrian images of the
same identity from different modalities. Existing works mainly focus on alleviating the …

Modern data augmentation using a mixture-based technique can regularize the models from
overfitting to the training data in various computer vision applications, but a proper data …

Visible-infrared person re-identification (VI-ReID) aims to search identities of pedestrians
across different spectra. In this task, one of the major challenges is the modality discrepancy …

Thanks for the cross-modal retrieval techniques, visible-infrared (RGB-IR) person re-
identification (Re-ID) is achieved by projecting them into a common space, allowing person …

Visible-infrared person re-identification (VI-ReID) is a challenging technology due to the
large gap between daytime visible modality and night-time infrared modality. Previous …

In this paper, we tackle the problem of discovering new classes in unlabeled visual data
given labeled data from disjoint classes. Existing methods typically first pre-train a model …

To tackle the challenge of vehicle re-identification (Re-ID) in complex lighting environments
and diverse scenes, multi-spectral sources like visible and infrared information are taken …

The RGB-infrared cross-modality person re-identification (ReID) task aims to recognize the
images of the same identity between the visible modality and the infrared modality. Existing …